Scale ML Infrastructure Engineer for Safe AI

Anthropic; New York (NY); Hybrid; USD 350,000 - 500,000; Full time

Benefits offered by this job

Equity donation matching

Vacation and parental leave

Flexible working hours

Office space

Job summary

Anthropic's Safeguards team seeks an engineer to own the infrastructure behind research in detection and mitigation of AI misuse. You will build the tooling researchers rely on to run experiments, train detectors, and select detections for launches.

You'll scale data pipelines and ML workloads, improve throughput and reliability of large-scale inference, and collaborate with researchers and engineers to evolve the stack as models change.

Qualifications

• Strong software engineering fundamentals and hands-on coding ability with Python.
• Experience building and operating data‑intensive or distributed systems in production.
• Experience building tooling or infrastructure used by other engineers or researchers.
• Comfort across the research-to-deployment pipeline, from experiments to production.
• Ability to debug performance and correctness problems across an unfamiliar stack.
• Strong written and verbal communication skills and collaborative decisions.

Responsibilities

• Build and scale the infrastructure and data pipelines behind Safeguards ML research.
• Own the training, evaluation, and scoring workflows used by researchers.
• Design tooling and interfaces for researchers to use directly.
• Build correctness and sanity checks so results stay trustworthy as models evolve.
• Take high-value research workflows from experiments to production-grade jobs.
• Improve throughput, cost, and reliability of large-scale inference and scoring workloads.
• Collaborate with researchers and engineers across Safeguards to anticipate needs.

Skills

Python

Distributed systems

Tooling/infrastructure

Research-to-production

Performance debugging

Communication skills

Education

Bachelor's degree

Job description

Anthropic's Safeguards team seeks an engineer to own the infrastructure behind research in detection and mitigation of AI misuse. You will build the tooling researchers rely on to run experiments, train detectors, and select detections for launches.

You'll scale data pipelines and ML workloads, improve throughput and reliability of large-scale inference, and collaborate with researchers and engineers to evolve the stack as models change.